Suchergebnisse

Abstract
The locations of minerals and mineral-forming environments, despite being of great scientific importance and economic interest, are often difficult to predict due to the complex nature of natural systems. In this work, we embrace the complexity and inherent "messiness" of our planet's intertwined geological, chemical, and biological systems by employing machine learning to characterize patterns embedded in the multidimensionality of mineral occurrence and associations. These patterns are a product of, and therefore offer insight into, the Earth's dynamic evolutionary history. Mineral association analysis quantifies high-dimensional multicorrelations in mineral localities across the globe, enabling the identification of previously unknown mineral occurrences, as well as mineral assemblages and their associated paragenetic modes. In this study, we have predicted (i) the previously unknown mineral inventory of the Mars analogue site, Tecopa Basin, (ii) new locations of uranium minerals, particularly those important to understanding the oxidation–hydration history of uraninite, (iii) new deposits of critical minerals, specifically rare earth element (REE)- and Li-bearing phases, and (iv) changes in mineralization and mineral associations through deep time, including a discussion of possible biases in mineralogical data and sampling; furthermore, we have (v) tested and confirmed several of these mineral occurrence predictions in nature, thereby providing ground truth of the predictive method. Mineral association analysis is a predictive method that will enhance our understanding of mineralization and mineralizing environments on Earth, across our solar system, and through deep time.

Objective We examine the relationships between contemporary progress in on‐road vehicle automation and its coherence with an envisioned "autopia" (automobile utopia) whereby the vehicle operation task is removed from all direct human control. Background The progressive automation of on‐road vehicles toward a completely driverless state is determined by the integration of technological advances into the private automobile market; improvements in transportation infrastructure and systems efficiencies; and the vision of future driving as a crash‐free enterprise. While there are many challenges to address with respect to automated vehicles concerning the remaining driver role, a considerable amount of technology is already present in vehicles and is advancing rapidly. Methods A multidisciplinary team of experts met to discuss the most critical challenges in the changing role of the driver, and associated safety issues, during the transitional phase of vehicle automation where human drivers continue to have an important but truncated role in monitoring and supervising vehicle operations. Results The group endorsed that vehicle automation is an important application of information technology, not only because of its impact on transportation efficiency, but also because road transport is a life critical system in which failures result in deaths and injuries. Five critical challenges were identified: driver independence and mobility, driver acceptance and trust, failure management, third-party testing, and political support. Conclusion Vehicle automation is not technical innovation alone, but is a social as much as a technological revolution consisting of both attendant costs and concomitant benefits.